| Literature DB >> 27293799 |
Abstract
Resource partitioning is well known along food and habitat for reducing competition among sympatric species, yet a study on temporal partitioning as a viable basis for reducing resource competition is not empirically investigated. Here, I attempt to identify the mechanism of temporal partitioning by intra- and interspecific diving analyses of three sympatric cormorant species at different freshwater wetlands around the Delhi region. Diving results indicated that cormorants opted for a shallow diving; consequently, they did not face any physiological stress. Moreover, diving durations were linked with seasons, foraging time and foraging habitats. Intraspecific comparison suggested that cormorants spent a longer time underwater in early hours of the day. Therefore, time spent for dive was higher in the forenoon than late afternoon, and the interspecific analysis also yielded a similar result. When Phalacrocorax niger and Phalacrocorax fuscicollis shared the same foraging habitat, they tended to differ in their foraging time (forenoon/afternoon). However, when P. niger and Phalacrocorax carbo shared the same foraging time, they tended to use different foraging habitats (lentic/lotic) leading to a mechanism of resource partitioning. Thus, sympatric cormorants effectively use time as a resource to exploit the food resources and successful coexistence.Entities:
Keywords: behaviour; cormorants; diving time; resource partition; sympatric; temporal
Year: 2016 PMID: 27293799 PMCID: PMC4892461 DOI: 10.1098/rsos.160175
Source DB: PubMed Journal: R Soc Open Sci ISSN: 2054-5703 Impact factor: 2.963
Figure 1.Numbers indicate the location of 15 freshwater wetlands and their corresponding names are: (1) Okhla Barrage Bird Sanctuary, (2) Indraprastha Thermal Power Station Pond, (3) Old Fort Lake, (4) Wazirabad Barrage, (5) Sonia Vihar, (6) Yamuna Biodiversity Park, (7) Jagatpur, (8) Bhatkal Lake, (9) Mandkaula, (10) Khanoli, (11) Bhindawas Bird Sanctuary, (12) Kharhar, (13) Sampla, (14) Mohamedabad and (15) Sheikha Jheel. State boundaries are shown by dotted lines. Inset shows the location of the study area (filled circle) in India.
Variations (mean ± s.d.) in the diving behaviour of three species of cormorants, their sample sizes are given in parenthesis (n.s., non-significant; CV, coefficient of variation).
| parameters | |||
|---|---|---|---|
| dive time (s)a | 14.72 ± 6.65 (538) | 19.82 ± 8.54 (204) | 18.26 ± 7.13 (270) |
| dive time CV (%) | 45 | 43 | 39 |
| pause time (s; n.s.) | 6.36 ± 3.82 (538) | 6.31 ± 3.2 (204) | 6.09 ± 2.78 (270) |
| pause time CV (%) | 60 | 51 | 46 |
| dives per bout (n.s.) | 16.3 ± 8.57 (33) | 15.69 ± 7.62 (13) | 15.89 ± 3.81 (17) |
| length of the bout (s; n.s.) | 356.1 ± 204.3 (33) | 410.2 ± 168.2 (13) | 386.7 ± 113.5 (17) |
| 2.74 | 3.52 | 3.28 |
GLM-ANOVA, p < 0.001.
Figure 2.Represents the types of diving adaptations observed in cormorant species. The ordinates represent the amount of time the cormorant remains underwater during diving, denoted as (TD), and the time it spends on the surface to replenish air for breathing immediately after the dive, denoted as (TP). The dotted line represents diving behaviour of marine cormorants [26,36]. The other three straight lines represent the linear regression fit-line using dive time (raw data) of cormorants.
Multiple regression analysis estimating the relationship of dependent variable TD with TP after controlling for the effect of difference in dive bouts. (Succeeding pause time (TP-Suc) indicates reactive dive; preceding pause time (TP-Pre) indicates anticipatory dive.)
| ANOVA | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| species | set | predictors | coefficient ± s.e. | model | d.f. | ||||
| 1 | 0.368 ± 0.0647 | 5.68 | 0.001 | 40.7 | 1, 504 | 32.25 | 0.001 | ||
| 2 | 0.368 ± 0.0647 | 5.69 | 0.001 | 40.8 | 1, 504 | 32.34 | 0.001 | ||
| 3 | −0.001 ± 0.0723 | −0.01 | 0.985 | 36.2 | 1, 468 | 0.000 | 0.985 | ||
| 1 | 0.250 ± 0.162 | 1.54 | 0.126 | 42.0 | 1, 190 | 2.360 | 0.126 | ||
| 2 | 0.255 ± 0.163 | 1.57 | 0.118 | 42.0 | 1, 190 | 2.460 | 0.118 | ||
| 3 | 0.396 ± 0.216 | 1.83 | 0.068 | 42.4 | 1, 178 | 3.360 | 0.068 | ||
| 1 | 0.569 ± 0.135 | 4.21 | 0.001 | 39.4 | 1, 252 | 17.74 | 0.001 | ||
| 2 | 0.566 ± 0.135 | 4.19 | 0.001 | 35.3 | 1, 252 | 17.57 | 0.001 | ||
| 3 | −0.029 ± 0.146 | −0.20 | 0.844 | 35.9 | 1, 235 | 0.400 | 0.844 | ||
Intraspecific variations (TD) of cormorants and corresponding dive time under different time slots. (Refer to figure 1 for the details of site numbers, and values in parenthesis are sample sizes. M-dash denotes insufficient data.)
| mean dive time under different time slots | |||||||
|---|---|---|---|---|---|---|---|
| species | site no | I (less than 11.00) | II (11.00–14.00) | III (14.00–16.00) | IV (greater than 16.00) | GLM-ANOVA | |
| 7 | 16.1 ± 6.3 (11) | 7.4 ± 1.7 (7) | 9.2 ± 3.3 (93) | 11.8 ± 5.03 (9) | |||
| versus | |||||||
| 1, 2, 11 | 17.8 ± 7.01 (23) | 23.8 ± 5.20 (17) | 20.1 ± 7.04 (33) | — | |||
| 7, 9, 10, 12 | 22.8 ± 6.8 (49) | 10.6 ± 2.05 (18) | 13.9 ± 5.3 (42) | 18.3 ± 10.3 (13) | |||
| versus | |||||||
*p < 0.05; **p < 0.001.
A nominal logistic regression model to explore the influence of intrinsic and extrinsic environmental factors on the diving behaviour of sympatric cormorants. (Log-likelihood = −898.990; test that all slopes are zero: G = 248.783, d.f. = 10, p-value = 0.001, dependent variables are species, coded as 0: P. niger; 1: P. fuscicollis; 2: P. carbo.)
| logit (1) | logit (2) | |||||
|---|---|---|---|---|---|---|
| predictors | co-efficient | s.d. | co-efficient | s.d. | ||
| constant | −1.275 | 0.338 | 0.001 | −1.682 | 0.331 | 0.001 |
| breeding seasons (breeding 1, non-breeding 2) | −0.689 | 0.212 | 0.001 | 0.712 | 0.168 | 0.001 |
| 0.092 | 0.124 | 0.000 | 0.058 | 0.012 | 0.001 | |
| −0.019 | 0.028 | 0.483 | −0.039 | 0.028 | 0.159 | |
| foraging time (forenoon-1, afternoon-2) | −0.497 | 0.112 | 0.001 | −0.139 | 0.103 | 0.177 |
| habitats (lentic-1, lotic-2) | 0.586 | 0.302 | 0.052 | 1.861 | 0.235 | 0.001 |